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A novel gait phase-based control strategy for a portable knee-ankle-foot robot

机译:一种新颖的基于步态相位的便携式膝踝足机器人控制策略

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This paper presents a novel control strategy of a portable knee-ankle-foot robot for overground gait training based on seven gait phases. Following assisted-as-needed (AAN) control strategies, the robot is able to provide assistance to the lower limbs in any gait phases, which deliver intensive training to certain lower-limb impairments. The gait phases can be detected in real time via inertia measurement unit (IMU) with hidden Markov model (HMM) and online Viterbi algorithm. The level of the robotic assistance adapts based on the kinematics of the lower limbs during overground walking. This control strategy has been tested on a healthy subject with an elastic bandage on the knee to simulate stiff knee condition of stroke patients. Adapting and increasing levels of assistance were provided to help the knee flex into a normal range. EMG profile of four major muscles on the assisted leg was collected. Experiment results indicate that the gait phase detection algorithm is accurate and robust and the robot is able to provide effective and synchronized assistance to the subject during overground walking.
机译:本文提出了一种基于七个步态阶段的用于地面步态训练的便携式膝踝足机器人的新型控制策略。遵循需要的辅助(AAN)控制策略,该机器人能够在任何步态阶段为下肢提供帮助,从而为某些下肢损伤提供强化训练。步态相位可以通过具有隐马尔可夫模型(HMM)的惯性测量单元(IMU)和在线维特比算法进行实时检测。机器人辅助的级别根据地面行走过程中下肢的运动学来调整。此控制策略已在健康受试者的膝盖上用弹性绷带进行了测试,以模拟中风患者的僵硬膝盖状况。提供了适应性增强的援助,以帮助膝盖屈伸至正常范围。收集了辅助腿上四个主要肌肉的肌电图。实验结果表明,步态相位检测算法准确,鲁棒,机器人能够在地面行走过程中为对象提供有效且同步的协助。

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